Recommender Systems Handbook (32 results)

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    Language: English

    Published by Springer, 2022

    1071621963 / 9781071621967

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    Hardcover. Condition: Good. 3rd edition. VG condition book without dust jacket. Boards are clean with little wear. Book has clean and bright contents.

  • Language: English

    Published by Springer-Verlag New York Inc., 2010

    0387858199 / 9780387858197

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    Encuadernación de tapa dura. Condition: Como Nuevo. Dust Jacket Condition: Como Nuevo.

  • Language: English

    Published by Springer, 2015

    1489976361 / 9781489976369

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    Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

  • Language: English

    Published by Springer, 2022

    1071621963 / 9781071621967

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    Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Language: English

    Published by Springer, 2022

    1071621963 / 9781071621967

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  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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  • Language: English

    Published by Springer-Verlag New York Inc., New York, 2022

    1071621963 / 9781071621967

    • Hardcover

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    Hardcover. Condition: new. Hardcover. This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

    Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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    Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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    Taschenbuch. Condition: Neu. Recommender Systems Handbook | Francesco Ricci (u. a.) | Taschenbuch | xi | Englisch | 2023 | Springer | EAN 9781071621998 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

    Seller: California Books, Miami, FL, U.S.A.California Books

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  • Language: English

    Published by Springer, Berlin, Springer US, Springer, 2015

    1489976361 / 9781489976369

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    Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems' major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

    Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.

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  • Language: English

    Published by Springer-Verlag New York Inc., New York, 2022

    1071621963 / 9781071621967

    • Hardcover

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    Hardcover. Condition: new. Hardcover. This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Language: English

    Published by SPRINGER NP, 2022

    1071621963 / 9781071621967

    • Hardcover
    • International Edition

    Seller: UK BOOKS STORE, London, LONDO, United KingdomUK BOOKS STORE

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    Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

  • Language: English

    Published by Springer-Nature New York Inc, 2023

    1071621998 / 9781071621998

    • Softcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Paperback. Condition: Brand New. 3rd edition. 1071 pages. 9.25x6.10x2.11 inches. In Stock.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods.The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation.This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.

  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

    • Softcover

    Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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  • Language: English

    Published by Springer, 2015

    1489976361 / 9781489976369

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    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Hardcover. Condition: Brand New. 1020 pages. 9.50x6.50x2.25 inches. In Stock.

  • Language: English

    Published by Springer, 2010

    0387858199 / 9780387858197

    • Hardcover

    Seller: Phatpocket Limited, Waltham Abbey, HERTS, United KingdomPhatpocket Limited

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    Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

  • Language: English

    Published by Springer, 2022

    1071621963 / 9781071621967

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  • Language: English

    Published by Springer, 2023

    1071621998 / 9781071621998

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  • Language: English

    Published by Springer, Berlin|Springer US|Springer, 2023

    1071621998 / 9781071621998

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation te.

  • Language: English

    Published by Springer US, New York, N.Y., 2022

    1071621963 / 9781071621967

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &Uumlber den AutorFrancesco Ricci is full professor at the Faculty of Computer Science, Free University of Bozen-Bolzano. F. Ricci has established in Bolzano a reference point for the research on Recommender Systems. He has co.

  • Language: English

    Published by Springer, Berlin, Springer US, Springer, 2015

    1489976361 / 9781489976369

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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems' major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems. 1003 pp. Englisch.

  • Language: English

    Published by Springer US, Springer US Apr 2022, 2022

    1071621963 / 9781071621967

    • Hardcover
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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods.The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation.This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. 1072 pp. Englisch.

  • Language: English

    Published by Springer US, Springer US Apr 2023, 2023

    1071621998 / 9781071621998

    • Softcover
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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods.The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation.This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. 1072 pp. Englisch.

  • Language: English

    Published by Springer, Springer Apr 2023, 2023

    1071621998 / 9781071621998

    • Softcover
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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods.The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation.This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 1072 pp. Englisch.